“R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law...

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“RATIONALITY AND REGULATION OF PAYDAY LOANS” Paige Marta Skiba Associate Professor of Law September 2011

Transcript of “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law...

Page 1: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

“RATIONALITY AND REGULATION OF PAYDAY LOANS”

Paige Marta Skiba

Associate Professor of Law

September 2011

Page 2: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

REGULATION

Bans Interest rate caps Loan-size restrictions Military constraints Loan lengths Information disclosures

Page 3: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

IMPERFECT INFORMATION IN SUBPRIME CREDIT

Information asymmetries are important in theory e.g. Stiglitz and Weiss, 1981

Ensuing credit market failures can create inefficiency at micro and macro level

Understanding causes liquidity constraints is important for policy responses

Page 4: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

IMPERFECT INFORMATION IN SUBPRIME CREDIT

Moral Hazard Individual borrowers are more likely to default on larger loans Borrowers do not internalize the default costs of larger loans

Adverse Selection Risky borrowers want to borrow a lot because default likely

Page 5: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

EMPIRICAL STRATEGY

The largest recommended loan is a discontinuous function of customer income.

Firms allow loans that are < ½ paycheck.And, loans come in $50increments

Customers with very similar incomes receive different size loans

Page 6: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

LOAN ELIGIBILITY

Page 7: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

EMPIRICAL STRATEGY

Regressing default on loan amount captures both MH and AS

OLS coefficient on loan size includes1) The causal effect of having a larger loan on the probability of

default ( MH)2) The correlation induced by observably equivalent borrowers taking

out different loans (with private information about their own risks = AS)

To separately identify the effect of MH, we isolate exogenous variation in loan amount

IV instruments loan amount with eligibility indicators, identifying the effect of the loan size holding selection contact (MH)

Page 8: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

REGRESSION RESULTS

OLS

Loan Amount 0.038***

(0.003)

Observations 13,246

IV (instrument = offer curve)

Loan Amount -0.041***

(0.014)

Observations 13,246

Page 9: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

RESULTS

No moral hazard $100 larger loan decreases probability of default by

4 percentage points

Adverse section Choosing a $100 larger loan increases probability of

default by 8 percentage points

Strong evidence of liquidity constraints An additional $1 of credit available

Borrow 50 centsThis is huge compared to literature

Page 10: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

REGULATION

Bans Interest rate caps Loan-size restrictions Military constraints Loan lengths Information disclosures

Page 11: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

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Page 12: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

REGULATION

Bans Interest rate caps Loan-size restrictions Military constraints Loan lengths Information disclosures

Page 13: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

ARMY PERSONNEL ARE MORE LIKELY TO DEFAULT

When controlling for loan length, credit score, loan size, pay frequency, and state, probability of renew and default and statistically significantly different.

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Page 14: “R ATIONALITY AND R EGULATION OF P AYDAY L OANS ” Paige Marta Skiba Associate Professor of Law September 2011.

REFLECTIONS ON EFFECTIVENESS OF PAYDAY LENDING CONSTRAINTS

Bans Misguided

Interest rate caps Essentially banning

Loan-size restrictions Larger loan better?

Military-specific rules ?

Loan lengths Longer or shorter loans doesn’t matter

Information disclosures Useless if care about rollovers